CN106710220B - A kind of urban road layering Dynamic coordinated control algorithm and control method - Google Patents
A kind of urban road layering Dynamic coordinated control algorithm and control method Download PDFInfo
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Abstract
The invention discloses a kind of urban road layering Dynamic coordinated control algorithm and control methods, and urban road is longitudinally divided into three layers, is laterally divided into different control work zones.According to real-time dynamic traffic data, dynamic updates the control parameter of each the sub-district control range and each sub-district of different layers, achievees the purpose that each layer traffic flow Dynamic coordinated control of urban road.Check analysis shows that urban road hierarchical coordinative control technology is obviously improved vehicle average speed, and each layer vehicle can quickly sail out of each sub-district, and urban road wagon flow congestion problems are effectively relieved.
Description
Technical field
The present invention relates to urban road transportation control field, in particular to a kind of urban road layering Dynamic coordinated control is calculated
Method and control method.
Background technique
Modern City Traffic network not only includes ordinary road, but also including only for the through street of vehicle fast passing,
This two classes road network is linked together by ring road, constitutes a complicated nonlinear time-varying big traffic network.Both therefore realize
Coordinated control, be of great significance for improving entire urban traffic conditions.
Currently, since there are the complexity of transportation network and nonlinear time-varying, domestic and international many for urban road
Person conducts in-depth research inhomogeneous urban road respectively.However existing alleviation urban road congestion method is generally only single
Solely one of research, does not comprehensively consider the two.Single research ordinary road has ignored city expressway fast passing energy
Power；Single research ring road then has ignored path optimization's ability of ordinary road.
Summary of the invention
Based on the above analysis, in order to alleviate urban traffic blocking, the invention proposes a kind of new urban road layering is dynamic
State traffic signal coordination and control method.Firstly, urban road by be longitudinally divided into ring road layer, ordinary road layer and through street layer.
Then, it devises a kind of function for ring road sub-area division and ring road layer is laterally divided into main ring road sub-district and from ring road sub-district；
Ordinary road is divided between different control work zones according to degree of association formula；In view of through street layer is without crossroad, and circle
Road entrance vehicle flowrate determines the wagon flow state of through street main line, therefore through street layer is incorporated to the processing of ring road layer, not to through street
It is transversely layered.Wherein use the simple and quick prediction downstream dynamic critical vehicle occupancy rate of BP neural network.Finally, with control work zone
Coordinated control is carried out to the traffic flow of each layer for unit.
Specifically, the purpose of the invention is achieved by the following technical solution:
A kind of urban road layering Dynamic coordinated control algorithm, it is characterised in that realized by following algorithm:
S1, for the function of ring road sub-area division
In formula: ENFor the opposite queue length of ring road i, EoFor the occupation rate in the downstream Entrance ramp i and the ratio of critical occupation rate
Value,For the sum of the two value；A(kc-1) it is corrected parameter, value, which is mainly detained vehicle by upper period ring road, to be influenced；For
Ratio of the sum of the current queue length of ring road i+u with the sum of maximum queue length, Ni(kc) it is kthcIt controls in the period, ring road i's
Queue length predicted value,The maximum queue length allowed for ring road i；It is kthcThe control downstream period ring road i dynamic is faced
The time occupancy of boundary's vehicle；Oi(kc) it is kthcIt controls in the period, the actual measurement occupation rate in the downstream ring road i；If ENOSForActivation
Threshold value, ENHSForActivation threshold, whenGreater than ENOSWhen, its upstream adjacent turn road ring road i is from ring road；WhenGreater than ENHS
When, its upstream adjacent turn road ring road i+u is from ring road；
The final local modulation amount of S2, main ring road sub-district adjusts the algorithm of the queue length of vehicle
In formula: qi(kc) be ring road i final local modulation amount；For kthcEntrance ramp allows to lead in the control period
The maximal regulated volume of traffic crossed；For ring road i kthcControl the maximum regulated quantity for being lined up control in the period；For kthc
It controls in the period, the Traffic Demand Forecasting value of ring road i；For dynamic critical occupation rate；
Wherein, dynamic critical occupation rateValue by BP neural network training method predict to obtain, it is specific as follows:
By kthcTime m in period is divided into { t1, t2..., tm, the collected data of different time sections are Oim, then
Oim=(o1, o2..., om), (m ∈ N+) (5)
N group, every group of M+1 data are classified as, and are met
N+M=m, (n ∈ N+, M ∈ N+) (6)
For pth therein, (p=1,2 ..., n) group is denoted as:
XP=[op, op+1..., op+M]T (7)
Choose XpThe preceding M inputs as BP neural network, the M+1 desired outputs as network then have
To n group data are divided into above, the input matrix collection X and target output matrix collection Y for the network being made of it are respectively
X=[X1, X2..., Xn] (9)
Y=[Y1, Y2..., Yn] (10)
The number for choosing network input layer, hidden layer and output layer neuron, establishes neural network, then utilizes nerve net
Network tool box carries out network training and obtains prediction result；
S3, adjusted from the final local modulation amount of ring road sub-district vehicle queue length algorithm
In formula: qi+u(kc) it is from the final local modulation amount of ring road i+u；For kthcThe period is controlled from ring road i+u's
Minimum is lined up control and regulation amount；KwFor control parameter；For kthcThe period is controlled, minimum be lined up being arranged from ring road i+1 is grown
Degree coordinates ring road group { i, i+1 ..., i+nj}；
The algorithm of S4, the adjacent intersection degree of association
In formula, DS(i→j)For the link counting degree of association in the direction i → j；DC(i-j)For the period between crossing i and crossing j
The degree of association: NE(i→j)For association wagon flow vehicle number already present on the section of the direction i → j, including queuing vehicle number and driving vehicle
Number can be obtained in real time by the magnetic induction coil that section is arranged；NA(i→j)For in next signal period on the section of the direction i → j
The most relevance wagon flow vehicle increment being likely to occur, needs to comprehensively consider road section traffic volume situation and intersection signal control parameter carries out
Prediction in real time；LVFor average traffic length；n1(i→j)Number of track-lines is occupied for the association wagon flow on the section of the direction i → j；L1(i→j)For i
The direction → j section lane total length；It is associated with and compensates for link counting corresponding to the total length of the direction i → j section lane
Coefficient；KNFor rate mu-factor；TmaxWith TminThe independent design signal period maximum and minimum of respectively crossing i and crossing j
Value；KCFor adjacent intersection signal period associated weights coefficient；
The algorithm of S5, the Multiple Intersections combination degree of association
In formula, DS (i, j ... .s, t)Total link counting degree of association between association crossing (i, j ... s, t)；
DC (i, j ... s, t)Total periodic associated degree in crossing between association crossing (i, j ... s, t)；Π is that even multiplication accords with；N is association
Crossing logarithm, i.e. association section number；It is kth to the link counting degree of association between association crossing, it is true by following formula (17)
It is fixed；For link counting degree of association composite function:
In formula, sort is ascending sort function, indicates to the link counting degree of association between association crossing to press n from small
It rearranges to big sequence, and is successively assigned to
S6, ordinary road control work zone division methods and common period, split calculation method of parameters, phase sequence optimization side
Case, wherein
Control work zone division methods are as follows:
H1, as the degree of association D between adjacent intersection i and crossing j(i, j)Threshold value D is separated less than or equal to adjacent intersectionTNSWhen, road
Mouth i and crossing j are not divided in same control work zone；
H2, as the degree of association D between adjacent intersection i and crossing j(i, j)More than or equal to adjacent intersection merging threshold DTNCWhen, road
Mouth i and crossing j are divided in same control work zone；
H3 is as the degree of association D between adjacent intersection i and crossing j(i, j)In DTNSWith DTNCBetween when, combined by Multiple Intersections
Whether the degree of association is greater than Multiple Intersections separation threshold value DTMS, determine whether crossing i and crossing j are divided in same control work zone；
Common period algorithm are as follows:
In formula, L is the loss time in one signal period of crossing, and Y is the sum of each phase flow-rate ratio in crossing, half of n
It turns around in left turn lane in periodic duty vehicle number (can monitor to obtain according to crossing), t leaves crossing for each car of turning left to turn around
Required time, r are corrected parameter；
The algorithm of split are as follows:
sitip=C*gip(i=1,2,3...；P=1,2,3,4) (20)
In formula, gipFor the split of crossing i phase p, sitipFor the green time of crossing i phase p, QipFor the vehicle of phase
Flow, Qip_zRing road vehicle flowrate, H are reached for crossing i phase pipFor the vehicle occupancy rate of phase, WipFor phase weights；
Phase sequence prioritization scheme:
It is classified as key crossing and non-key crossing according to the criticality difference of ordinary road layer crossroad, it is crucial
The common period at crossing is the optimal period of control work zone, and the crossroad that ring road layer is connected with ordinary road layer is set as crucial
Crossing, phase sequence are optimization phase sequence scheme, remaining ordinary road layer four crossway is non-key crossing, and phase sequence is general phase sequence scheme；
S7, the subinterval coordinated control by different layers, determine key crossing optimal period and each phase green time, meter
The guidance speed of different layers is calculated, guidance speed calculation method is
In formula, VpzFor the guidance speed of ordinary road ring road layer, VzkFor the guidance speed of ring road layer, it is assumed that by crossing i to
Section between the i+1 of crossing is that sub-district is connected section.Li_i+1Indicate the distance between control work zone interval section i_i+1, LsxTable
Show the distance of ring road of unilateral be connected or more, LpzIndicate distance of the ordinary road to ring road, Ci+1Sub-district where indicating crossing i+1
Common period, CiThe common period of sub-district, t where indicating crossing iiWhen indicating the up-run lane starting of crossing i, the fortune of crossing i
Row time, Pi+1_p1It turns around queue length for the vehicle left-hand rotation in 1 lane of crossing i+1 phase,Ring road is driven towards for crossing i phase p
When the vehicle that is detained of ring road, t is the time needed for each car sails out of crossroad.
Further, in the S6 control work zone division methods and common period, split calculation method of parameters, public week
Corrected parameter r in phase algorithm is using ANFIS (Adaptive neuro-fuzzy inference system) come cbr signal period, step
Are as follows: first setting training samples number, then determine output number of samples, then in training sample according to vehicle number, repair
The just different settings of preceding signal period and flow-rate ratio can make ANFIS generate reasonable degree of membership and obscure by sample training
Secondly rule turns around occupation rate input ANFIS inference system according to the crossing flow-rate ratio that measures and left-hand rotation, after can calculating optimization
Signal period, for revised Period Formula establish ANFIS inference system, each crossing signals period inferred, choosing
Common signal period C of the maximum value as the control work zone is selected, all crossings are used uniformly the common signal period in the sub-district.
A kind of urban road layering Dynamic coordinated control technology, it is characterised in that realized by following steps:
Step 1 is divided into ordinary road layer, ring road layer and fast by demixing technology and integrally considering from city, by urban road
Fast road floor；
Step 2 is according to the formula D of S4 adjacent intersection algorithm of correlation degree(i→j)Ordinary road major trunk roads are divided into different sons
Area；
Step 3 according to claim 1 in, the S6 ordinary road control work zone division methods and common period, split
Calculation method of parameters, phase sequence prioritization scheme calculate common period C, the key crossing phase sequence at each crossing of ordinary road major trunk roads
Prioritization scheme and each phase green time sitip；
The cycle set of key crossing is the optimal period of control work zone according to the calculated result of step 3 by step 4, general
The each sub-district common period of passway major trunk roads should be consistent with key crossing common period, determines best common period C with thisi；
Step 5 calculates ring road queue length activation threshold E for the function of ring road sub-area division according to S1NOSAnd ENHS,
Ring road is divided into different principal and subordinate's ring road sub-districts.
Step 6 adjusts the algorithm of the queue length of vehicle according to the final local modulation amount of the main ring road sub-district of S2, passes through BP mind
The simple and quick prediction ring road downstream vehicle dynamic critical occupation rate of method through network training
Step 7 according to the final local modulation amount of the main ring road sub-district of S2 adjust vehicle queue length algorithm and S3 from ring road
The final local modulation amount of sub-district adjusts the algorithm of the queue length of vehicle to calculate the final local modulation amount q of principal and subordinate's ring road sub-districti
(kc) and qi+u(kc) judge whether principal and subordinate's ring road sub-district vehicle queue overflows, if overflowing return step 4 adjusts crossroad most
Good common period and each phase green time；
Step 8, by the subinterval coordinated control of different layers, determines that the optimal period of key crossing and each phase are green according to S7
The lamp time calculates the guidance speed of different layers, carries out coordinated control to urban road.
The present invention compared with the prior art, have the following advantages that and the utility model has the advantages that
1, in S1, by introducing corrected parameter A (kc-1), expand activation threshold range, to increase ramp metering rate sub-district
Range；
2, in S2, the number of network input layer, hidden layer and output layer neuron is chosen, establishes neural network, then
Prediction result is obtained by BP neural network training using Neural Network Toolbox, simplifies dynamic critical occupation rateMeter
Calculation process, and improve the rapidity and accuracy of prediction；
3, in S6, the common signal period is shortened using revised Period Formula, to reduce vehicle waiting signal
The lamp time, while also shortening the queue length of each crossroad vehicle；By introducing ordinary road crossroad phase
Ring road vehicle amount adjustment split formula is driven towards, to reduce the appearance that ring road is lined up spillover；
To sum up, the present invention can be such that vehicle average speed is obviously improved, and each layer vehicle can quickly sail out of each sub-district, effectively
Alleviate urban road wagon flow congestion problems.
Detailed description of the invention
Fig. 1 is urban road hierarchical diagram of the invention.
Fig. 2 is BP neural network schematic diagram of the invention.
Fig. 3 is general phase sequence conceptual scheme of the invention.
Fig. 4 is optimization phase sequence conceptual scheme of the invention.
Fig. 5 is that ordinary road layer of the invention is averaged passage speed-mechanical periodicity situation map.
Fig. 6 is that ring road layer of the invention is averaged passage speed-mechanical periodicity situation map.
Specific embodiment
In conjunction with attached drawing, with Zhengzhou West 3rd Ring Road north section ordinary road layer major trunk roads, ordinary road layer branch and through street layer circle
For road, acquisition traffic data in April is described in further detail the present invention, but embodiments of the present invention are not limited to
This.
Embodiment
As shown in Figure 1, Figure 2, Figure 3 and Figure 4, a kind of urban road is layered Dynamic coordinated control technology, it is characterised in that logical
Cross following steps realization:
Urban road is divided into ordinary road layer, circle by demixing technology as shown in Figure 1, integrally consider from city by step 1
Channel layer and through street layer；
Step 2 is according to S4 adjacent intersection algorithm of correlation degree
In formula, Ds(i→j)For the link counting degree of association in the direction i → j；Dc(i→j)For the period between crossing i and crossing j
The degree of association: NE(i→j)For association wagon flow vehicle number already present on the section of the direction i → j, including queuing vehicle number and driving vehicle
Number can be obtained in real time by the magnetic induction coil that section is arranged；NA(i→j)For in next signal period on the section of the direction i → j
The most relevance wagon flow vehicle increment being likely to occur, needs to comprehensively consider road section traffic volume situation and intersection signal control parameter carries out
Prediction in real time；LVFor average traffic length；n1(i→j)Number of track-lines is occupied for the association wagon flow on the section of the direction i → j；L1(i→j)For i
The direction → j section lane total length；It is associated with and compensates for link counting corresponding to the total length of the direction i → j section lane
Coefficient；KNFor rate mu-factor；TmaxWith TminThe independent design signal period maximum and minimum of respectively crossing i and crossing j
Value；KCFor adjacent intersection signal period associated weights coefficient；
Ordinary road major trunk roads are divided into different sub-districts；
Step 3 is according to S6 ordinary road control work zone division methods and common period, split calculation method of parameters, phase sequence
Prioritization scheme, wherein
Control work zone division methods are as follows:
H1, as the degree of association D between adjacent intersection i and crossing j(i, j)Threshold value D is separated less than or equal to adjacent intersectionTNSWhen, road
Mouth i and crossing j are not divided in same control work zone；
H2, as the degree of association D between adjacent intersection i and crossing j(i, j)More than or equal to adjacent intersection merging threshold DTNCWhen, road
Mouth i and crossing j are divided in same control work zone；
H3 is as the degree of association D between adjacent intersection i and crossing j(i, j)In DTNSWith DTNCBetween when, combined by Multiple Intersections
Whether the degree of association is greater than Multiple Intersections separation threshold value DTMS, determine whether crossing i and crossing j are divided in same control work zone；
Common period algorithm are as follows:
In formula, L is the loss time in one signal period of crossing, and Y is the sum of each phase flow-rate ratio in crossing, half of n
It turns around in left turn lane in periodic duty vehicle number (can monitor to obtain according to crossing), t leaves crossing for each car of turning left to turn around
Required time, r are corrected parameter；
The algorithm of split are as follows:
sitip=C*gip(i=1,2,3...；P=1,2,3,4) (20)
In formula, gipFor the split of crossing i phase p, sitipFor the green time of crossing i phase p, QipFor the vehicle of phase
Flow, Qip_zRing road vehicle flowrate, H are reached for crossing i phase pipFor the vehicle occupancy rate of phase, WipFor phase weights；
Phase sequence optimization:
It is classified as key crossing and non-key crossing according to the criticality difference of ordinary road layer crossroad, it is crucial
The common period at crossing is the optimal period of control work zone, and the crossroad that ring road layer is connected with ordinary road layer is set as crucial
Crossing, phase sequence are optimization phase sequence scheme, as shown in figure 4, remaining ordinary road layer four crossway is non-key crossing, phase sequence is general
Phase sequence scheme, as shown in Figure 3；
Calculate common period C, key crossing phase sequence prioritization scheme and each phase at each crossing of ordinary road major trunk roads
Green time sitip；
The cycle set of key crossing is the optimal period of control work zone according to the calculated result of step 3 by step 4, general
The each sub-district common period of passway major trunk roads should be consistent with key crossing common period, determines best common period C with thisi；
Step 5 is used for the function of ring road sub-area division according to the S1
In formula: ENFor the opposite queue length of ring road i, EoFor the occupation rate in the downstream Entrance ramp i and the ratio of critical occupation rate
Value,For the sum of the two value；A(kc-1) it is corrected parameter, value, which is mainly detained vehicle by upper period ring road, to be influenced；For
Ratio of the sum of the current queue length of ring road i+u with the sum of maximum queue length, Ni(kc) it is kthcIt controls in the period, ring road i's
Queue length predicted value,The maximum queue length allowed for ring road i；It is kthcControl the downstream period ring road i dynamic
The time occupancy of critical vehicle；Oi(kc) it is kthcIt controls in the period, the actual measurement occupation rate in the downstream ring road i；If ENoSForSwash
Threshold value living, ENHSForActivation threshold, whenGreater than ENOSWhen, its upstream adjacent turn road ring road i is from ring road；WhenGreater than ENHS
When, its upstream adjacent turn road ring road i+u is from ring road；
To calculate ring road queue length activation threshold ENOSAnd ENHS, ring road is divided into different principal and subordinate's ring road sub-districts；
Step 6 adjusts the algorithm of the queue length of vehicle according to the final local modulation amount of the main ring road sub-district of the S2
In formula: qi(kc) be ring road i final local modulation amount；For kthcEntrance ramp allows to lead in the control period
The maximal regulated volume of traffic crossed；For ring road i kthcControl the maximum regulated quantity for being lined up control in the period；For kthc
It controls in the period, the Traffic Demand Forecasting value of ring road i；For dynamic critical occupation rate；
Wherein, dynamic critical occupation rateValue measured in advance by the method for BP neural network training as shown in Figure 2
It arrives, specific as follows:
By kthcTime m in period is divided into { t1, t2..., tm, the collected data of different time sections are Oim, then
Oim=(o1, o2..., om), (m ∈ N+) (5)
N group, every group of M+1 data are classified as, and are met
N+M=m, (n ∈ N+, M ∈ N+) (6)
For pth therein, (p=1,2 ..., n) group, are denoted as:
XP=[op, op+1..., op+M]T (7)
Choose XpThe preceding M inputs as BP neural network, the M+1 desired outputs as network then have
To n group data are divided into above, the input matrix collection X and target output matrix collection Y for the network being made of it are respectively
X=[X1, X2..., Xn] (9)
Y=[Y1, Y2..., Yn] (10)
The number for choosing network input layer, hidden layer and output layer neuron, establishes neural network, then utilizes nerve net
Network tool box carries out network training and obtains prediction result；
Simple and quick prediction ring road downstream vehicle dynamic critical occupation rate
Step 7 adjusts the algorithm of the queue length of vehicle according to the final local modulation amount of the main ring road sub-district of the S2
In formula: qi(kc) be ring road i final local modulation amount；For kthcEntrance ramp allows to lead in the control period
The maximal regulated volume of traffic crossed；For ring road i kthcControl the maximum regulated quantity for being lined up control in the period；For kthc
It controls in the period, the Traffic Demand Forecasting value of ring road i；For dynamic critical occupation rate；
S3 adjusts the algorithm of the queue length of vehicle from the final local modulation amount of ring road sub-district
In formula: qi+u(kc) it is from the final local modulation amount of ring road i+u；For kthcThe period is controlled from ring road i+u's
Minimum is lined up control and regulation amount；KwFor control parameter；For kthcThe period is controlled, minimum be lined up being arranged from ring road i+1 is grown
Degree coordinates ring road group { i, i+1 ..., i+nj}；
To calculate the final local modulation amount q of principal and subordinate's ring road sub-districti(kc) and qi+u(kc) judge that principal and subordinate's ring road sub-district vehicle is arranged
Whether team overflows, if overflowing return step 4 adjusts the best common period in crossroad and each phase green time；
Step 8 determines the optimal period and each phase of key crossing according to the subinterval coordinated control of the S7 different layers
Green time calculates the guidance speed of different layers
In formula, VpzFor the guidance speed of ordinary road ring road layer, VzkFor the guidance speed of ring road layer, it is assumed that by crossing i to
Section between the i+1 of crossing is that sub-district is connected section.Li_i+1Indicate the distance between control work zone interval section i_i+1, LsxTable
Show the distance of ring road of unilateral be connected or more, LpzIndicate distance of the ordinary road to ring road, Ci+1Sub-district where indicating crossing i+1
Common period, CiThe common period of sub-district, t where indicating crossing iiWhen indicating the up-run lane starting of crossing i, the fortune of crossing i
Row time, pi+1_p1It turns around queue length for the vehicle left-hand rotation in 1 lane of crossing i+1 phase, Pip_PzRing road is driven towards for crossing i phase p
When the vehicle that is detained of ring road, t is the time needed for each car sails out of crossroad；
It calculates the guidance speed of different layers, coordinated control is carried out to urban road.
Zhengzhou West 3rd Ring Road north section ordinary road layer major trunk roads, ordinary road layer branch and through street layer ring road traffic in April
Flow data acquisition statistics such as table 1:
1 different layers traffic flow data of table
Using urban road layering Dynamic coordinated control algorithm of the invention and control technology, acquisition data are tested
It calculates.
The vehicle queue number that each phase in each crossing is assumed when beginning is 0, wherein ordinary road layer and ring road layer carry out respectively
Checking computations, each case carry out 10 checking computations, and each simulation time is 7200s.The limit of ordinary road layer is assumed during checking computations
Speed processed is 60km/h, and ring road layer restricted speed is 80km/h.The ordinary road major trunk roads carry out control work zone when decentralised control
Average speed 25km/h.
As shown in figure 5, after using the method for the present invention, ordinary road layer average speed-mechanical periodicity situation.
As shown in fig. 6, after using the method for the present invention, ring road layer is averaged passage speed-mechanical periodicity situation.
Meanwhile 10 checking computation results of the speed of different layers are as shown in table 2:
The longitudinal layered average speed checking computation results of table 2
It is general after being layered Dynamic coordinated control technology using urban road proposed by the present invention it can be seen from checking computation results
The average speed of passway layer is 54km/h, and 25km/h when relative to decentralised control improves 113%, dynamic relative to arterial highway
The 38km/h of state Coordinated Control, improves 42%, the sub-district dynamic patitioning algorithm relative to Philodendron ‘ Emerald Queen'
48.32km/h and 39.54km/h, improves 12% and 37%.The average speed of ring road layer is 65km/h, and speed is ideal.
Checking computations explanation, is obviously improved, each layer vehicle can quickly sail out of each sub-district, be effectively relieved using the method for the present invention rear vehicle speed
Urban road traffic congestion.
It should be understood by those skilled in the art that the present invention is not limited to the above embodiments, above-described embodiment and explanation
It is merely illustrated the principles of the invention described in book, without departing from the spirit and scope of the present invention, the present invention also has
Various changes and modifications, these changes and improvements all fall within the protetion scope of the claimed invention.The claimed scope of the invention
It is defined by the appending claims and its equivalent thereof.
Claims (3)
1. a kind of urban road is layered Dynamic coordinated control algorithm, it is characterised in that realized by following algorithm:
S1, for the function of ring road sub-area division
In formula: ENFor the opposite queue length of ring road i, EoFor the downstream Entrance ramp i occupation rate and critical occupation rate ratio,For the sum of the two value；A(kc-1) it is corrected parameter, value, which is mainly detained vehicle by upper period ring road, to be influenced；For ring road
Ratio of the sum of the current queue length of i+u with the sum of maximum queue length, Ni(kc) it is kthcIt controls in the period, the queuing of ring road i
Length prediction value,The maximum queue length allowed for ring road i；It is kthcControl the downstream period ring road i dynamic critical vehicle
Time occupancy；oi(kc) it is kthcIt controls in the period, the actual measurement occupation rate in the downstream ring road i；If ENOSForActivation threshold,
ENHsForActivation threshold, whenGreater than ENOSWhen, its upstream adjacent turn road ring road i is from ring road；WhenGreater than ENHSWhen, ring road i
Its upstream adjacent turn road+u is from ring road；
The final local modulation amount of S2, main ring road sub-district adjusts the algorithm of the queue length of vehicle
In formula: qi(kc) be ring road i final local modulation amount；For kthcControl the period in Entrance ramp allow by
The maximal regulated volume of traffic；For ring road i kthcControl the maximum regulated quantity for being lined up control in the period；For kthcControl
In period, the Traffic Demand Forecasting value of ring road i；For dynamic critical occupation rate；
Wherein, dynamic critical occupation rateValue by BP neural network training method predict to obtain, it is specific as follows:
By kthcTime m in period is divided into { t1, t2..., tm, the collected data of different time sections are Oim, then
Oim=(o1, o2..., om), (m ∈ N+) (5)
N group, every group of M+1 data are classified as, and are expired
Foot
N+M=m, (n ∈ N+, M ∈ N+) (6)
For pth therein, (p=1,2 ..., n) group is denoted as:
XP=[op, op+1..., op+M]T (7)
Choose XpThe preceding M inputs as BP neural network, the M+1 desired outputs as network then have
To the n group data being divided into, the input matrix collection X and target output matrix collection Y for the network being made of it are respectively
X=[X1, X2..., Xn] (9)
Y=[Y1, Y2..., Yn] (10)
The number for choosing network input layer, hidden layer and output layer neuron, establishes neural network, then utilizes neural network work
Tool case carries out network training and obtains prediction result；
S3, adjusted from the final local modulation amount of ring road sub-district vehicle queue length algorithm
In formula: qi+u(kc) it is from the final local modulation amount of ring road i+u；For kthcControl minimum of the period from ring road i+u
It is lined up control and regulation amount；KwFor control parameter；For kthcThe period is controlled, the minimum queue length being arranged from ring road i+1,
Coordinate ring road group { i, i+1 ..., i+nj}；
The algorithm of S4, the adjacent intersection degree of association
In formula, DS(i→j)For the link counting degree of association in the direction i → j；DC(i→j)It is periodic associated between crossing i and crossing j
Degree: NE(i→j)It, can for association wagon flow vehicle number already present on the section of the direction i → j, including queuing vehicle number and driving vehicle number
It is obtained in real time with the magnetic induction coil being arranged by section；NA(i→j)It is possible in next signal period on the section of the direction i → j
The most relevance wagon flow vehicle increment of appearance, needs to comprehensively consider road section traffic volume situation and intersection signal control parameter carries out in real time
Prediction；LVFor average traffic length；n1(i→j)Number of track-lines is occupied for the association wagon flow on the section of the direction i → j；L1(i→j)For i → side j
To section lane total length；Penalty coefficient is associated with for link counting corresponding to the total length of the direction i → j section lane；KN
For rate mu-factor；TmaxWith TminThe independent design signal period maximal and minmal value of respectively crossing i and crossing j；KCFor
Adjacent intersection signal period associated weights coefficient；
The algorithm of S5, the Multiple Intersections combination degree of association
In formula, DS (i, j ... .s, t)Total link counting degree of association between association crossing (i, j ... s, t)；DC (i, j ... .s, t)For
It is associated with the periodic associated degree in crossing total between crossing (i, j ... s, t)；Π is that even multiplication accords with；N is association crossing logarithm, that is, is closed
Join section number；It is kth to the link counting degree of association between association crossing, is determined by following formula (17)；For section friendship
Flux degree of association composite function:
In formula, sort is ascending sort function, is indicated n to the link counting degree of association between association crossing by from small to large
Sequence rearrange, and be successively assigned to
S6, ordinary road control work zone division methods and common period, split calculation method of parameters, phase sequence prioritization scheme,
In,
Control work zone division methods are as follows:
H1, as the degree of association D between adjacent intersection i and crossing j(i, j)Threshold value D is separated less than or equal to adjacent intersectionTNSWhen, crossing i
It is not divided in same control work zone with crossing j；
H2, as the degree of association D between adjacent intersection i and crossing j(i, j)More than or equal to adjacent intersection merging threshold DTNCWhen, crossing i
Same control work zone is divided in crossing j；
H3 is as the degree of association D between adjacent intersection i and crossing j(i, j)In DTNSWith DTNCBetween when, pass through Multiple Intersections combination association
Whether degree, which is greater than Multiple Intersections, separates threshold value DTMS, determine whether crossing i and crossing j are divided in same control work zone；
Common period algorithm are as follows:
In formula, L is the loss time in one signal period of crossing, and Y is the sum of each phase flow-rate ratio in crossing, and n is half period
Vehicle number (can monitor to obtain according to crossing) is turned around in left turn lane in running, t leaves needed for crossing for each car of turning left to turn around
Time, r is corrected parameter；
The algorithm of split are as follows:
sitip=C*gip(i=1,2,3...；P=1,2,3,4) (20)
In formula, gipFor the split of crossing i phase p, sitipFor the green time of crossing i phase p, QipFor the vehicle flowrate of phase,
Qip_zRing road vehicle flowrate, H are reached for crossing i phase pipFor the vehicle occupancy rate of phase, WipFor phase weights；
Phase sequence optimization:
Key crossing and non-key crossing, key crossing are classified as according to the criticality difference of ordinary road layer crossroad
Common period be control work zone optimal period, the crossroad that ring road layer is connected with ordinary road layer is set as critical path
Mouthful, phase sequence is optimization phase sequence scheme, remaining ordinary road layer four crossway is non-key crossing, and phase sequence is general phase sequence scheme；
S7, the subinterval coordinated control by different layers, determine key crossing optimal period and each phase green time, calculate not
The guidance speed of same layer, guidance speed calculation method are
In formula, VpzFor the guidance speed of ordinary road ring road layer, VzkFor the guidance speed of ring road layer, it is assumed that by crossing i to crossing i
Section between+1 is that sub-district is connected section, Li_i+1Indicate the distance between control work zone interval section i_i+1, LsxIndicate single
The distance of the connected ring road up and down in side, LpzIndicate distance of the ordinary road to ring road, Ci+1Sub-district is public where indicating crossing i+1
Period, CiThe common period of sub-district, t where indicating crossing iiWhen indicating the up-run lane starting of crossing i, when the operation of crossing i
Between, pi+1_p1It turns around queue length for the vehicle left-hand rotation in 1 lane of crossing i+1 phase,Circle when driving towards ring road for crossing i phase p
The vehicle that road is detained, t are the time needed for each car sails out of crossroad.
2. a kind of urban road according to claim 1 is layered Dynamic coordinated control algorithm, it is characterised in that the S6 control
In system limited region dividing method and common period, split calculation method of parameters, the corrected parameter r in common period algorithm is used
ANFIS (Adaptive neuro-fuzzy inference system) carrys out the cbr signal period, the steps include: that number of training is arranged first
Amount, then determine output number of samples, then in training sample according to vehicle number, amendment before signal period and flow-rate ratio
Different settings ANFIS can be made to generate reasonable degree of membership and fuzzy rule, secondly according to the road measured by sample training
Mouthful flow-rate ratio and left-hand rotation are turned around occupation rate input ANFIS inference system, the signal period after can calculating optimization, after amendment
Period Formula establish ANFIS inference system, in each crossing signals period inferred, select maximum value as the control work zone
Common signal period C, all crossings are used uniformly the common signal period in the sub-district.
3. a kind of urban road with the layering Dynamic coordinated control algorithm of urban road described in claim 1 is layered dynamic coordinate
Control method, it is characterised in that realized by following steps:
Step 1 passes through demixing technology and integrally considers from city, and urban road is divided into ordinary road layer, ring road layer and through street
Layer；
Step 2 according to claim 1 in, the formula D of the S4 adjacent intersection algorithm of correlation degree(i→j)Ordinary road major trunk roads are drawn
It is divided into different sub-districts；
Step 3 according to claim 1 in, the S6 ordinary road control work zone division methods and common period, split parameter
Calculation method, phase sequence prioritization scheme come calculate each crossing of ordinary road major trunk roads common period C, key crossing phase sequence optimization
Scheme and each phase green time sitip；
The cycle set of key crossing is the optimal period of control work zone, common road according to the calculated result of step 3 by step 4
The each sub-district common period of road major trunk roads should be consistent with key crossing common period, determines best common period C with thisi；
Step 5 according to claim 1 in, function of the S1 for ring road sub-area division calculates ring road queue length threshold of activation
Value ENOSAnd ENHS, ring road is divided into different principal and subordinate's ring road sub-districts；
Step 6 according to claim 1 in, the final local modulation amount of the main ring road sub-district of S2 adjusts the calculation of the queue length of vehicle
Method passes through the prediction ring road downstream vehicle dynamic critical occupation rate that the method for BP neural network training is simple and quick
Step 7 according to claim 1 in, the final local modulation amount of the main ring road sub-district of S2 adjusts the calculation of the queue length of vehicle
The algorithm for the queue length that method and S3 adjust vehicle from the final local modulation amount of ring road sub-district is final to calculate principal and subordinate's ring road sub-district
Local modulation amount qi(kc) and qi+u(kc) judge whether principal and subordinate's ring road sub-district vehicle queue overflows, it is adjusted if overflowing return step 4
The whole best common period in crossroad and each phase green time；
Step 8 according to claim 1 in, the subinterval coordinated control of different layers is determined the best week of key crossing by the S7
Phase and each phase green time, calculate the guidance speed of different layers, carry out coordinated control to urban road.
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| CN111145548B (en) * | 2019-12-27 | 2021-06-01 | 银江股份有限公司 | Important intersection identification and subregion division method based on data field and node compression |
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